Maintenance chain integration using Petri-net enabled multiagent system modeling and implementation approach

Engineering asset management (EAM) is a broad discipline and the EAM functions and processes are characterized by its distributed nature. However, engineering asset nowadays mostly relies on self-maintained experiential rule bases and periodic maintenance, which is lacking a collaborative engineering approach. This research proposes a collaborative environment integrated by a service center with domain expertise such as diagnosis, prognosis, and asset operations. The collaborative maintenance chain combines asset operation sites, service center (i.e., maintenance operation coordinator), system provider, first tier collaborators, and maintenance part suppliers. Meanwhile, to realize the automation of communication and negotiation among organizations, multiagent system (MAS) technique is applied to enhance the entire service level. During the MAS design processes, this research combines Prometheus MAS modeling approach with Petri-net modeling methodology and unified modeling language to visualize and rationalize the design processes of MAS. The major contributions of this research include developing a Petri-net enabled Prometheus MAS modeling methodology and constructing a collaborative agent-based maintenance chain framework for integrated EAM.

From critique to cultural recovery: critical futures studies and casual layered analysis

Critical futures studies is not about the careers of a few scholars, rather it is about projects that transcend the narrow boundaries of the self. This biographical monograph examines the life and work of Richard Slaughter and Sohail Inayatullah.

Modeling and analyzing the carbon footprint of business processes

Many corporations and individuals realize that environmental sustainability is an urgent problem to address. In this chapter, we contribute to the emerging academic discussion by proposing two innovative approaches for engaging in the development of environmentally sustainable business processes. Specifically, we describe an extended process modeling approach for capturing and documenting the dioxide emissions produced during the execution of a business process. For illustration, we apply this approach to the case of a government Shared Service provider. Second, we then introduce an analysis method for measuring the carbon dioxide emissions produced during the execution of a business process. To illustrate this approach, we apply it in the real-life case of a European airport and show how this information can be leveraged in the re-design of "green" business processes.

Modeling and Analyzing the Carbon Footprint of Business Processes

Many corporations and individuals realize that environmental sustainability is an urgent problem to address. In this chapter, we contribute to the emerging academic discussion by proposing two innovative approaches for engaging in the development of environmentally sustainable business processes. Specifically, we describe an extended process modeling approach for capturing and documenting the dioxide emissions produced during the execution of a business process. For illustration, we apply this approach to the case of a governmental Shared Services provider. Second, we then introduce an analysis method for measuring the carbon dioxide emissions produced during the execution of a business process. To illustrative this approach, we apply it in the real-life case of an European airport and show how this information can be leveraged in the re-design of “green” busi-ness processes.

Role of kilometer-scale weak circular heterogeneities on upper crustal deformation patterns: Evidence from scaled analogue modeling and the Sudbury Basin, Canada

The Sudbury Basin is a non-cylindrical fold basin occupying the central portion of the Sudbury Impact Structure. The impact structure lends itself excellently to explore the structural evolution of continental crust containing a circular region of long-term weakness. In a series of scaled analogue experiments various model crustal configurations were shortened horizontally at a constant rate. In mechanically weakened crust, model basins formed that mimic several first-order structural characteristics of the Sudbury Basin: (1) asymmetric, non-cylindrical folding of the Basin, (2) structures indicating concentric shortening around lateral basin termini and (3) the presence of a zone of strain concentration near the hinge zones of model basins. Geometrically and kinematically this zone corresponds to the South Range Shear Zone of the Sudbury Basin. According to our experiments, this shear zone is a direct mechanical consequence of basin formation, rather than the result of thrusting following folding. Overall, the models highlight the structurally anomalous character of the Sudbury Basin within the Paleoproterozoic Eastern Penokean Orogen. In particular, our models suggest that the Basin formed by pure shear thickening of crust, whereas transpressive deformation prevailed elsewhere in the orogen. The model basin is deformed by thickening and non-cylindrical synformal buckling, while conjugate transpressive shear zones propagated away from its lateral tips. This is consistent with pure shear deformation of a weak circular inclusion in a strong matrix. The models suggest that the Sudbury Basin formed as a consequence of long-term weakening of the upper crust by meteorite impact.

Near-Wall Turbulent Pressure Diffusion Modeling and Influence in Three-Dimensional Secondary Flows

The purpose of this paper is to develop a second-moment closure with a near-wall turbulent pressure diffusion model for three-dimensional complex flows, and to evaluate the influence of the turbulent diffusion term on the prediction of detached and secondary flows. A complete turbulent diffusion model including a near-wall turbulent pressure diffusion closure for the slow part was developed based on the tensorial form of Lumley and included in a re-calibrated wall-normal-free Reynolds-stress model developed by Gerolymos and Vallet. The proposed model was validated against several one-, two, and three-dimensional complex flows.

Modeling and detection of complex attacks

A complex attack is a sequence of temporally and spatially separated legal and illegal actions each of which can be detected by various IDS but as a whole they constitute a powerful attack. IDS fall short of detecting and modeling complex attacks therefore new methods are required. This paper presents a formal methodology for modeling and detection of complex attacks in three phases: (1) we extend basic attack tree (AT) approach to capture temporal dependencies between components and expiration of an attack, (2) using enhanced AT we build a tree automaton which accepts a sequence of actions from input message streams from various sources if there is a traversal of an AT from leaves to root, and (3) we show how to construct an enhanced parallel automaton that has each tree automaton as a subroutine. We use simulation to test our methods, and provide a case study of representing attacks in WLANs.

Porohyperelastic analysis to explore mechanical properties of chondrocytes using numerical modeling and experiments : a finite element study

There are many continuum mechanical models have been developed such as liquid drop models, solid models, and so on for single living cell biomechanics studies. However, these models do not give a fully approach to exhibit a clear understanding of the behaviour of single living cells such as swelling behaviour, drag effect, etc. Hence, the porohyperelastic (PHE) model which can capture those aspects would be a good candidature to study cells behaviour (e.g. chondrocytes in this study). In this research, an FEM model of single chondrocyte cell will be developed by using this PHE model to simulate Atomic Force Microscopy (AFM) experimental results with the variation of strain rate. This material model will be compared with viscoelastic model to demonstrate the advantages of PHE model. The results have shown that the maximum value of force applied of PHE model is lower at lower strain rates. This is because the mobile fluid does not have enough time to exude in case of very high strain rate and also due to the lower permeability of the membrane than that of the protoplasm of chondrocyte. This behavior is barely observed in viscoelastic model. Thus, PHE model is the better model for cell biomechanics studies.

Modeling and multiway analysis of chatroom tensors

This work identifies the limitations of n-way data analysis techniques in multidimensional stream data, such as Internet chat room communications data, and establishes a link between data collection and performance of these techniques. Its contributions are twofold. First, it extends data analysis to multiple dimensions by constructing n-way data arrays known as high order tensors. Chat room tensors are generated by a simulator which collects and models actual communication data. The accuracy of the model is determined by the Kolmogorov-Smirnov goodness-of-fit test which compares the simulation data with the observed (real) data. Second, a detailed computational comparison is performed to test several data analysis techniques including svd [1], and multi-way techniques including Tucker1, Tucker3 [2], and Parafac [3].

Melanocortin-1 receptor genotype is a risk factor for basal and squamous cell carcinoma

MC1R gene variants have previously been associated with red hair and fair skin color, moreover skin ultraviolet sensitivity and a strong association with melanoma has been demonstrated for three variant alleles that are active in influencing pigmentation: Arg151Cys, Arg160Trp, and Asp294His. This study has confirmed these pigmentary associations with MC1R genotype in a collection of 220 individuals drawn from the Nambour community in Queensland, Australia, 111 of whom were at high risk and 109 at low risk of basal cell carcinoma and squamous cell carcinoma. Comparative allele frequencies for nine MC1R variants that have been reported in the Caucasian population were determined for these two groups, and an association between prevalence of basal cell carcinoma, squamous cell carcinoma, solar keratosis and the same three active MC1R variant alleles was demonstrated [odds ratio = 3.15 95% CI (1.7, 5.82)]. Three other commonly occurring variant alleles: Val60Leu, Val92Met, and Arg163Gln were identified as having a minimal impact on pigmentation phenotype as well as basal cell carcinoma and squamous cell carcinoma risk. A significant heterozygote effect was demonstrated where individuals carrying a single MC1R variant allele were more likely to have fair and sun sensitive skin as well as carriage of a solar lesion when compared with those individuals with a consensus MC1R genotype. After adjusting for the effects of pigmentation on the association between MC1R variant alleles and basal cell carcinoma and squamous cell carcinoma risk, the association persisted, confirming that presence of at least one variant allele remains informative in terms of predicting risk for developing a solar-induced skin lesion beyond that information wained through observation of pigmentation phenotype.

Error modeling and calibration of exteroceptive sensors for accurate mapping applications

Reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. In field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. This is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. The whole system is as reliable as the weakest link in this chain. In this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as LIDAR or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. The coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. This allows the mapping accuracy to be calculated at run time. A generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. This allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. The mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. The techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. Consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. © 2009 Wiley Periodicals, Inc.